Skill UI

This skill automates the entire GitHub Pull Request (PR) review cycle, specifically targeting Copilot Code Review comments. It runs a robust loop: automatically triggering reviews, triaging open threads, dispatching parallel fixes that adhere to repo conventions, committing changes, and resolving comments. It continues iterating until the PR is deemed clean and ready for merge, minimizing manual effort and ensuring high code quality.

A comprehensive guide for advanced econometric techniques in causal inference, covering modern approaches for quasi-experimental designs such as staggered Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Double Machine Learning (DML). It details best practices, critical diagnostic tests (e.g., weak instruments, parallel trend checks, bias decomposition), and robust reporting standards required for high-impact economic research.

This guide provides a comprehensive backward planning workflow for submitting a full paper to the ACM/IEEE HRI conference. It warns researchers that the most critical and time-consuming steps—such as IRB approval, participant recruitment, and data collection—must be planned months in advance, often taking longer than the writing process. It maps out the entire academic cycle, from initial abstract submission through to camera-ready preparation, including parallel tracks like alt.HRI and Late-Breaking Reports.

A comprehensive guide for authors submitting to top-tier computer vision conferences (like ICCV). It details the new single-deadline workflow, emphasizing the parallel production of code and videos. Learn how to structure supplementary materials for maximum reviewer impact, including detailed ablation studies, failure mode galleries, and maintaining strict double-blind anonymity in the archive.

This guide details the advanced methodology for structuring the 'Related Work' section for top-tier academic conferences (e.g., ASPLOS). It emphasizes positioning research across multiple parallel domains—including architecture, OS/systems, compilers, and accelerators—and defining the precise technical boundary where your work advances the state of the art.

A comprehensive guide for strengthening causal claims in corporate and empirical finance research. This resource details advanced econometric methods—including IV, DiD, RDD, and natural experiments—and provides strategies to preempt common methodological attacks (e.g., endogeneity, parallel-trends violations) required by top-tier academic journals like the Journal of Finance.

This comprehensive guide outlines the rigorous methodology required for designing high-impact evaluations of parallel systems and algorithms for top-tier conferences. It stresses that contributions must demonstrate the 'twin bar': both concurrency correctness (e.g., linearizability) and measurable scalability (e.g., strong vs. weak scaling). It covers best practices for establishing strong baselines, managing measurement hygiene (variance, pinning), and anticipating advanced reviewer scrutiny in HPC.

A comprehensive guide for researchers detailing how to structure the 'Related Work' section for top-tier parallel computing conferences like PPoPP. It emphasizes 'delta-first' comparison, covering specific technical lanes (concurrent data structures, runtimes, GPU acceleration, memory models), and ensuring proper academic positioning against major parallel systems venues.

This guide outlines the necessary steps to ensure that parallel computing performance papers are scientifically reproducible. Since parallel results depend heavily on machine architecture, topology, and runtime conditions, proper documentation must cover everything from CPU/GPU specifications and interconnects to thread pinning policies, random seeds, and compiler flags. The focus is on proving the scaling trend, not just the absolute numbers, allowing results to hold true across different hardware platforms.

A comprehensive deep dive into the PPoPP conference review pipeline. This guide models the single-round, double-blind review process, detailing how submissions are evaluated by the Program Committee and External Review Committee. It covers critical aspects such as the author response rebuttal, automatic poster consideration, and the specific technical axes reviewers prioritize (e.g., scalability, concurrency correctness, baseline honesty) for parallel programming research.

This guide helps researchers determine the correct academic venue for their work in parallel and concurrent computing. It clarifies the scope of PPoPP versus related conferences (CGO, PLDI, ASPLOS, HPCA, POPL, etc.) by asking: 'Is the parallelism the point, or is it the setting?' Use this framework to distinguish contributions focused on parallel algorithms, compiler optimization, concurrency theory, or hardware microarchitecture.

A comprehensive guide detailing the rigorous standards required for submitting parallel programming research to top-tier academic venues. It covers crucial topics such as proving concurrency correctness, demonstrating measurable scalability using speedup curves, adhering to strict formatting (10 pages, two-column layout), and structuring the technical contribution to satisfy expert reviewers.